The Arnoldi process is an iterative algorithm used to construct an orthonormal basis for a Krylov subspace, which is crucial in numerical linear algebra for approximating eigenvalues and eigenvectors of large matrices. This process helps reduce the dimensionality of problems, making computations more efficient while preserving important properties of the original matrix.
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